class_docstr: Unit tests for distributions in continuous.py 
class_docstr_tok: ["Unit","tests","for","distributions","in","continuous.py"]
docstr: Tests random sampling from Multivariate Normal distribution 
docstr_tok: ["Tests","random","sampling","from","Multivariate","Normal","distribution"]
code: def test_rand_sampling_multi_normal(self):
      """Tests random sampling from Multivariate Normal distribution"""
      self.report(
          "Test random sampling of Multivariate Normal Distribution."
      )
      cov_thresh = 0.1
      mean_thresh = 0.01
      mean = np.arange(3)
      covariance = 3 * np.identity(3)
      dist = MultivariateGaussian(mean, covariance)
      samples = dist.draw_samples("random", self.size)
      mean_r = self._compute_mean(samples, 0)
      self._check_sample_sizes(samples)
      assert (
          abs(mean - self._compute_mean(samples, 0)) <= mean_thresh
      ).all()
      assert (
          abs(covariance - self._compute_covariance(samples))
          <= cov_thresh
      ).all()
      self.report(
          "%s :: test result: mean=%s" % (str(dist), str(mean_r)),
          "test_result",
      )
  
file_path: dragonfly/dragonfly/distributions/unittest_continuous.py
imports: from __future__ import absolute_import
  import unittest
  import numpy
  import warnings
  from .continuous import Beta, ContinuousUniform, Exponential, Normal, MultivariateGaussian
  from ..utils.base_test_class import BaseTestClass, execute_tests
label_desc: Use image node_id 7 for calling the ContinuousDistributionsTestCase obj's underlying member method code with example usage: obj.test_rand_sampling_multi_normal() without return types